Overview
This workflow automates the monitoring and analysis of local events by integrating web scraping, AI-powered data processing, and seamless data storage. It leverages Bright Data MCP for event data extraction and OpenAI for intelligent analysis, streamlining the identification of sponsorship opportunities.
Key Features
- Automated Event Scraping: Uses Bright Data MCP to collect event data from specified URLs.
- AI-Driven Analysis: Employs OpenAI models to evaluate and rate events for sponsorship suitability.
- Data Organization: Splits and processes individual event items for granular analysis.
- Seamless Storage: Saves analyzed events and sponsorship ratings directly to Google Sheets for easy access and reporting.
- Manual and Automated Triggers: Supports both manual initiation and automated execution for flexible operation.
Benefits
- Time Savings: Eliminates manual event research and analysis, reducing hours of repetitive work.
- Enhanced Decision-Making: AI-driven insights help prioritize high-value sponsorship opportunities.
- Centralized Data: Consolidates event intelligence in Google Sheets for collaboration and tracking.
- Scalable Automation: Easily adapts to monitor new sources or expand analysis criteria.
Use Cases
- Marketing teams seeking local sponsorships.
- Event managers tracking partnership opportunities.
- Agencies automating event intelligence gathering.
Integrations
- Bright Data MCP, OpenAI, Google Sheets, LangChain, n8n core nodes.
